Introductory Statistics with Randomization and Simulation

Bringing a fresh approach to intro statistics, ISRS introduces inference faster using randomization and simulation techniques

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A new book, Introduction to Modern Statistics (IMS is available on the web, as a PDF, and in paperback), represents the evolution of Introductory Statistics with Randomization and Simulation (ISRS). For those who are considering adopting Introductory Statistics with Randomization and Simulation, we recommend Introduction to Modern Statistics instead.

There aren't any immediate plans for material changes to ISRS or its distribution, though this book is now de-emphasized in our catalog, e.g. moved to last in our list of books available. We are starting to think about what the right distribution changes, if any, might be as we encourage people to move towards IMS, but it's too early for us to consider implementing any such changes. The earliest we would consider any major change is mid-2022, and even then, we intend to proceed with caution to minimize disruptions. If you do have direct feedback or thoughts, such as what would be useful to you to switch to IMS -- or why that isn't something you want to do -- we appreciate the feedback through our Contact page.


Getting Started

Amazon KDP is raising print prices by ≈40% in mid-June. As a result, we will be raising this book's B&W paperback price to  to $25 to align with our other textbooks and compensate for the increased costs. Despite the price increases on the OpenIntro titles, and while this book will be seeing a larger increase than the other books, we expect margins net our costs to decrease our overall OpenIntro operating margins. That is, in total, the many tens of thousands of dollars that students will pay for these price increases each year will benefit Amazon, not OpenIntro, and OpenIntro will likely lose money on net revenue/costs as a result of these price changes. As a result of this change, we are also more aggressively exploring alternative printers to Amazon that provide better quality books as well as selling more books outside of Amazon.

Videos and slides are shared across books. Don't fret if you see a different section number than the one you expect: check the title and you'll see it is covering the topic of interest.

All of our website / resource links to Amazon are affiliate links. When you shop on Amazon using these links, we receive a small commission at no extra charge to you.

 FREE -- Textbook PDF

If you want to skip the optional contribution, set the price to $0

 $8.50 -- B&W paperback

Available on Amazon and in select bookstores

List of known textbook typos

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Data sets

List of data sets and the option to download files

Where to find more data sets

An incredible list of data organized by Shonda Kuiper


Teachers: General Resources


Teachers: Sample Exams


What is Statistics?


Chapter 1: Intro to Data

 1.1 - Using stents to prevent strokes

Real case study with a surprising finding

 1.2 - Data basics

Typical data structures and properties

 1.3 - Data collection principles

Thoughtful data collection is critical to learning from data

 1.4 - Sampling principles and strategies

Different ways to sample from a population

 1.5 - Experiments

Basic principles of experimental design

 1.6 - Examining numerical data

Mean, standard deviation, histograms, box plots, and more

 1.7 - Considering categorical data

Table proportions, bar graphs, mosaic plots, and more

  Slides 1A - Intro to data

LaTeX slides for full chapter on Github

  Slides 1B - Summarizing data

LaTeX slides for full chapter on Github

  Slides 1.1 - Intro to data, case study

Google Slides version, can export to Powerpoint

  Slides 1.2 - Data Basics

Google Slides version, can export to Powerpoint

  Slides 1.3 + 1.4 - Sampling principles and strategies

Google Slides version, can export to Powerpoint

  Slides 1.5 - Experiments

Google Slides version, can export to Powerpoint

  Slides 1.6 - Examining numerical_data

Google Slides version, can export to Powerpoint

  Slides 1.7 - Considering categorical data

Google Slides version, can export to Powerpoint

 Lab - Intro to Statistical Software

Software: R (Base), R (Tidyverse), Rguroo, Jamovi, JASP, SAS, Stata

 Lab - Introduction to data

Software: R (Base), R (Tidyverse), Rguroo, Jamovi, JASP, Python, SAS, Stata

Weighted mean

Supplemental section: How and when to use weighting


Chapter 2: Foundations for Inference


Chapter 3: Inference for Categorical Data


Chapter 4: Inference for Numerical Data


Chapter 5: Introduction to Linear Regression


Chapter 6: Multiple and Logistic Regression


More Student Resources


Course Resources


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